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Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016
The state of Mato Grosso is Brazil’s agribusiness powerhouse with a cattle herd of 30.2 million head in 2017. With land use patterns heavily influenced by beef production, which requires substantial land inputs, the state is a key target for environmental conservation. Yet the spatial and temporal d...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490905/ https://www.ncbi.nlm.nih.gov/pubmed/31039156 http://dx.doi.org/10.1371/journal.pone.0215286 |
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author | Vale, Petterson Gibbs, Holly Vale, Ricardo Munger, Jacob Brandão, Amintas Christie, Matthew Florence, Eduardo |
author_facet | Vale, Petterson Gibbs, Holly Vale, Ricardo Munger, Jacob Brandão, Amintas Christie, Matthew Florence, Eduardo |
author_sort | Vale, Petterson |
collection | PubMed |
description | The state of Mato Grosso is Brazil’s agribusiness powerhouse with a cattle herd of 30.2 million head in 2017. With land use patterns heavily influenced by beef production, which requires substantial land inputs, the state is a key target for environmental conservation. Yet the spatial and temporal dynamics of slaughterhouses in Mato Grosso remain largely unknown due to data limitations. Here, we provide a novel method to map slaughterhouse expansion and contraction. We analyzed the opening and closing of 133 plants between 1967 and 2016 in Mato Grosso and estimated the geographic locations and slaughter volumes. This was achieved by triangulating across multiple data sources including a registry of 21 million companies, government records of three million slaughter transactions (Portuguese acronym GTA), and high resolution satellite imagery. Our study is the first to include longitudinal information and both inspected (for food quality) and uninspected slaughterhouses. The results show that 72 plants operated in 2016 through 52 holding companies. By measuring geographic distances between active plants and pasture areas, we documented a 29% increase in the density of plants during 2000–2016, showing an expansion of the cattle slaughter infrastructure. We identified three periods of expansion: 1967–1995, with 15.1% of the plant openings; 1996–2003, with 24.6%; and 2004–2016, with 60.3%. While closings likely occurred throughout the period studied, no data were available prior to 2002. We estimated a minimum value for the volume of uninspected slaughter as 2–3% for 2013–2016. We conclude by discussing potential applications of the data, a deidentified version of which is made available through an online repository. The method developed here can be replicated for the whole country, which would increase our understanding of the dynamics of cattle slaughter and their impact on land use. |
format | Online Article Text |
id | pubmed-6490905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-64909052019-05-17 Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016 Vale, Petterson Gibbs, Holly Vale, Ricardo Munger, Jacob Brandão, Amintas Christie, Matthew Florence, Eduardo PLoS One Research Article The state of Mato Grosso is Brazil’s agribusiness powerhouse with a cattle herd of 30.2 million head in 2017. With land use patterns heavily influenced by beef production, which requires substantial land inputs, the state is a key target for environmental conservation. Yet the spatial and temporal dynamics of slaughterhouses in Mato Grosso remain largely unknown due to data limitations. Here, we provide a novel method to map slaughterhouse expansion and contraction. We analyzed the opening and closing of 133 plants between 1967 and 2016 in Mato Grosso and estimated the geographic locations and slaughter volumes. This was achieved by triangulating across multiple data sources including a registry of 21 million companies, government records of three million slaughter transactions (Portuguese acronym GTA), and high resolution satellite imagery. Our study is the first to include longitudinal information and both inspected (for food quality) and uninspected slaughterhouses. The results show that 72 plants operated in 2016 through 52 holding companies. By measuring geographic distances between active plants and pasture areas, we documented a 29% increase in the density of plants during 2000–2016, showing an expansion of the cattle slaughter infrastructure. We identified three periods of expansion: 1967–1995, with 15.1% of the plant openings; 1996–2003, with 24.6%; and 2004–2016, with 60.3%. While closings likely occurred throughout the period studied, no data were available prior to 2002. We estimated a minimum value for the volume of uninspected slaughter as 2–3% for 2013–2016. We conclude by discussing potential applications of the data, a deidentified version of which is made available through an online repository. The method developed here can be replicated for the whole country, which would increase our understanding of the dynamics of cattle slaughter and their impact on land use. Public Library of Science 2019-04-30 /pmc/articles/PMC6490905/ /pubmed/31039156 http://dx.doi.org/10.1371/journal.pone.0215286 Text en © 2019 Vale et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Vale, Petterson Gibbs, Holly Vale, Ricardo Munger, Jacob Brandão, Amintas Christie, Matthew Florence, Eduardo Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016 |
title | Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016 |
title_full | Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016 |
title_fullStr | Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016 |
title_full_unstemmed | Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016 |
title_short | Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016 |
title_sort | mapping the cattle industry in brazil’s most dynamic cattle-ranching state: slaughterhouses in mato grosso, 1967-2016 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490905/ https://www.ncbi.nlm.nih.gov/pubmed/31039156 http://dx.doi.org/10.1371/journal.pone.0215286 |
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